Overview

Dataset statistics

Number of variables11
Number of observations2100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory180.6 KiB
Average record size in memory88.1 B

Variable types

Numeric11

Alerts

ALTV is highly overall correlated with MSTV and 1 other fieldsHigh correlation
ASTV is highly overall correlated with MSTVHigh correlation
DL is highly overall correlated with MSTV and 1 other fieldsHigh correlation
MSTV is highly overall correlated with ALTV and 3 other fieldsHigh correlation
Width is highly overall correlated with ALTV and 2 other fieldsHigh correlation
AC has 829 (39.5%) zerosZeros
FM has 1217 (58.0%) zerosZeros
UC has 314 (15.0%) zerosZeros
DL has 1153 (54.9%) zerosZeros
ALTV has 1150 (54.8%) zerosZeros
MLTV has 124 (5.9%) zerosZeros
Tendency has 1035 (49.3%) zerosZeros

Reproduction

Analysis started2024-04-21 17:30:33.109679
Analysis finished2024-04-21 17:30:47.107112
Duration14 seconds
Software versionydata-profiling vv4.7.0
Download configurationconfig.json

Variables

LB
Real number (ℝ)

Distinct151
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean133.27964
Minimum105
Maximum161
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2024-04-21T23:00:47.191899image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum105
5-th percentile119
Q1126
median133
Q3140
95-th percentile149
Maximum161
Range56
Interquartile range (IQR)14

Descriptive statistics

Standard deviation9.9766692
Coefficient of variation (CV)0.074855163
Kurtosis-0.191265
Mean133.27964
Median Absolute Deviation (MAD)7
Skewness0.01931347
Sum279887.24
Variance99.533928
MonotonicityNot monotonic
2024-04-21T23:00:47.338321image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
133 129
 
6.1%
130 105
 
5.0%
122 102
 
4.9%
138 98
 
4.7%
125 87
 
4.1%
128 80
 
3.8%
142 74
 
3.5%
120 73
 
3.5%
132 71
 
3.4%
136 69
 
3.3%
Other values (141) 1212
57.7%
ValueCountFrequency (%)
105 4
 
0.2%
106 6
 
0.3%
106.0015807 1
 
< 0.1%
109.7830926 1
 
< 0.1%
110 19
0.9%
110.3333736 1
 
< 0.1%
112 16
0.8%
114 11
0.5%
114.9909543 1
 
< 0.1%
115 26
1.2%
ValueCountFrequency (%)
161 6
0.3%
160 1
 
< 0.1%
159 9
0.4%
158.7576656 1
 
< 0.1%
158 9
0.4%
157 3
 
0.1%
156.8623559 1
 
< 0.1%
156 4
0.2%
154 8
0.4%
152.0998698 1
 
< 0.1%

AC
Real number (ℝ)

ZEROS 

Distinct1038
Distinct (%)49.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0031482332
Minimum-0.008474577
Maximum0.014124295
Zeros829
Zeros (%)39.5%
Negative29
Negative (%)1.4%
Memory size16.5 KiB
2024-04-21T23:00:47.490474image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-0.008474577
5-th percentile0
Q10
median0.001643413
Q30.005649718
95-th percentile0.011067312
Maximum0.014124295
Range0.022598872
Interquartile range (IQR)0.005649718

Descriptive statistics

Standard deviation0.003844989
Coefficient of variation (CV)1.2213165
Kurtosis0.39504536
Mean0.0031482332
Median Absolute Deviation (MAD)0.001643413
Skewness1.0551698
Sum6.6112897
Variance1.4783941 × 10-5
MonotonicityNot monotonic
2024-04-21T23:00:47.637635image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 829
39.5%
0.014124295 35
 
1.7%
0.000834028 13
 
0.6%
0.00500417 9
 
0.4%
0.005838198 9
 
0.4%
0.002502085 9
 
0.4%
0.003336113 7
 
0.3%
0.001668057 7
 
0.3%
0.004170142 7
 
0.3%
0.007506255 7
 
0.3%
Other values (1028) 1168
55.6%
ValueCountFrequency (%)
-0.008474577 4
0.2%
-0.000184863 1
 
< 0.1%
-0.000155735 1
 
< 0.1%
-0.000122252 1
 
< 0.1%
-0.000117563 1
 
< 0.1%
-0.00011692 1
 
< 0.1%
-0.000112305 1
 
< 0.1%
-0.000108699 1
 
< 0.1%
-0.00010001 1
 
< 0.1%
-9.09 × 10-51
 
< 0.1%
ValueCountFrequency (%)
0.014124295 35
1.7%
0.014067995 1
 
< 0.1%
0.014064698 1
 
< 0.1%
0.014023732 1
 
< 0.1%
0.013861386 1
 
< 0.1%
0.013844515 1
 
< 0.1%
0.013819095 1
 
< 0.1%
0.013812155 1
 
< 0.1%
0.013757524 1
 
< 0.1%
0.013745704 1
 
< 0.1%

FM
Real number (ℝ)

ZEROS 

Distinct464
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.001563728
Minimum-0.0038387857
Maximum0.0063979762
Zeros1217
Zeros (%)58.0%
Negative52
Negative (%)2.5%
Memory size16.5 KiB
2024-04-21T23:00:47.796084image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-0.0038387857
5-th percentile0
Q10
median0
Q30.0025567343
95-th percentile0.0063979762
Maximum0.0063979762
Range0.010236762
Interquartile range (IQR)0.0025567343

Descriptive statistics

Standard deviation0.0024763291
Coefficient of variation (CV)1.5836061
Kurtosis-0.24149574
Mean0.001563728
Median Absolute Deviation (MAD)0
Skewness1.1292439
Sum3.2838288
Variance6.132206 × 10-6
MonotonicityNot monotonic
2024-04-21T23:00:47.953269image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1217
58.0%
0.00639797625 335
 
16.0%
0.000834028 10
 
0.5%
0.003336113 9
 
0.4%
0.001668057 9
 
0.4%
-0.00383878575 7
 
0.3%
0.005838198 7
 
0.3%
0.002502085 6
 
0.3%
0.001096491 5
 
0.2%
0.00500417 5
 
0.2%
Other values (454) 490
23.3%
ValueCountFrequency (%)
-0.00383878575 7
0.3%
-0.003434785 1
 
< 0.1%
-0.002888621 1
 
< 0.1%
-0.002467201 1
 
< 0.1%
-0.002303558 1
 
< 0.1%
-0.002075516 1
 
< 0.1%
-0.001776124 1
 
< 0.1%
-0.001686962 1
 
< 0.1%
-0.00159252 1
 
< 0.1%
-0.001544789 1
 
< 0.1%
ValueCountFrequency (%)
0.00639797625 335
16.0%
0.006272401 1
 
< 0.1%
0.006222222 1
 
< 0.1%
0.006183746 1
 
< 0.1%
0.00618238 1
 
< 0.1%
0.006153846 1
 
< 0.1%
0.006105006 1
 
< 0.1%
0.006072874 1
 
< 0.1%
0.006060606 1
 
< 0.1%
0.006031363 1
 
< 0.1%

UC
Real number (ℝ)

ZEROS 

Distinct1346
Distinct (%)64.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.004367135
Minimum-0.005219342
Maximum0.013600538
Zeros314
Zeros (%)15.0%
Negative13
Negative (%)0.6%
Memory size16.5 KiB
2024-04-21T23:00:48.092194image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-0.005219342
5-th percentile0
Q10.0018454468
median0.0044964175
Q30.0065530835
95-th percentile0.0092882137
Maximum0.013600538
Range0.01881988
Interquartile range (IQR)0.0047076367

Descriptive statistics

Standard deviation0.0030064738
Coefficient of variation (CV)0.68843161
Kurtosis-0.44398334
Mean0.004367135
Median Absolute Deviation (MAD)0.0022603395
Skewness0.1480531
Sum9.1709835
Variance9.0388846 × 10-6
MonotonicityNot monotonic
2024-04-21T23:00:48.255816image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 314
 
15.0%
0.000834028 24
 
1.1%
0.001668057 15
 
0.7%
0.002502085 12
 
0.6%
0.004170142 10
 
0.5%
0.013600538 9
 
0.4%
0.003336113 8
 
0.4%
0.00500417 7
 
0.3%
0.005952381 6
 
0.3%
0.005464481 6
 
0.3%
Other values (1336) 1689
80.4%
ValueCountFrequency (%)
-0.005219342 4
0.2%
-0.000131558 1
 
< 0.1%
-0.000100599 1
 
< 0.1%
-9.35 × 10-51
 
< 0.1%
-6.3 × 10-51
 
< 0.1%
-4.2 × 10-51
 
< 0.1%
-3.57 × 10-51
 
< 0.1%
-3.12 × 10-51
 
< 0.1%
-1.16 × 10-51
 
< 0.1%
-2.19 × 10-61
 
< 0.1%
ValueCountFrequency (%)
0.013600538 9
0.4%
0.012987013 1
 
< 0.1%
0.012622721 1
 
< 0.1%
0.012072435 1
 
< 0.1%
0.012048193 1
 
< 0.1%
0.011969532 1
 
< 0.1%
0.011764706 1
 
< 0.1%
0.011725293 1
 
< 0.1%
0.011709602 1
 
< 0.1%
0.011703511 1
 
< 0.1%

DL
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct701
Distinct (%)33.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00177252
Minimum-0.004942353
Maximum0.008237255
Zeros1153
Zeros (%)54.9%
Negative36
Negative (%)1.7%
Memory size16.5 KiB
2024-04-21T23:00:48.428440image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-0.004942353
5-th percentile0
Q10
median0
Q30.0033039768
95-th percentile0.008237255
Maximum0.008237255
Range0.013179608
Interquartile range (IQR)0.0033039768

Descriptive statistics

Standard deviation0.0026756275
Coefficient of variation (CV)1.5095048
Kurtosis0.33115676
Mean0.00177252
Median Absolute Deviation (MAD)0
Skewness1.2314063
Sum3.722292
Variance7.1589823 × 10-6
MonotonicityNot monotonic
2024-04-21T23:00:48.589746image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1153
54.9%
0.008237255 118
 
5.6%
0.000834028 22
 
1.0%
-0.004942353 6
 
0.3%
0.001668057 6
 
0.3%
0.002502085 5
 
0.2%
0.004282655 4
 
0.2%
0.006666667 4
 
0.2%
0.003336113 4
 
0.2%
0.004504505 3
 
0.1%
Other values (691) 775
36.9%
ValueCountFrequency (%)
-0.004942353 6
0.3%
-0.00012386 1
 
< 0.1%
-0.000110488 1
 
< 0.1%
-8.01 × 10-51
 
< 0.1%
-6.83 × 10-51
 
< 0.1%
-6.67 × 10-51
 
< 0.1%
-6.19 × 10-51
 
< 0.1%
-6.08 × 10-51
 
< 0.1%
-5.9 × 10-51
 
< 0.1%
-5.87 × 10-51
 
< 0.1%
ValueCountFrequency (%)
0.008237255 118
5.6%
0.008196721 2
 
0.1%
0.008187135 1
 
< 0.1%
0.008143322 1
 
< 0.1%
0.00811359 1
 
< 0.1%
0.008108108 1
 
< 0.1%
0.008103728 1
 
< 0.1%
0.008086253 1
 
< 0.1%
0.008077544 1
 
< 0.1%
0.008038585 1
 
< 0.1%

ASTV
Real number (ℝ)

HIGH CORRELATION 

Distinct182
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.975493
Minimum-11.5
Maximum104.5
Zeros0
Zeros (%)0.0%
Negative5
Negative (%)0.2%
Memory size16.5 KiB
2024-04-21T23:00:48.740750image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-11.5
5-th percentile21
Q132
median49
Q361
95-th percentile75
Maximum104.5
Range116
Interquartile range (IQR)29

Descriptive statistics

Standard deviation17.631292
Coefficient of variation (CV)0.37532958
Kurtosis-0.67933391
Mean46.975493
Median Absolute Deviation (MAD)14
Skewness-0.016110988
Sum98648.536
Variance310.86246
MonotonicityNot monotonic
2024-04-21T23:00:48.888144image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
65 60
 
2.9%
58 57
 
2.7%
60 57
 
2.7%
64 56
 
2.7%
61 53
 
2.5%
63 51
 
2.4%
51 49
 
2.3%
62 47
 
2.2%
22 45
 
2.1%
25 45
 
2.1%
Other values (172) 1580
75.2%
ValueCountFrequency (%)
-11.5 5
0.2%
11.79984559 1
 
< 0.1%
12 1
 
< 0.1%
13 7
0.3%
14 4
 
0.2%
15 4
 
0.2%
16 12
0.6%
17 12
0.6%
17.01339791 1
 
< 0.1%
18 9
0.4%
ValueCountFrequency (%)
104.5 5
 
0.2%
87 1
 
< 0.1%
86 4
 
0.2%
84 6
 
0.3%
83 4
 
0.2%
82 2
 
0.1%
81 7
0.3%
80 7
0.3%
79 15
0.7%
78.04997553 1
 
< 0.1%

MSTV
Real number (ℝ)

HIGH CORRELATION 

Distinct133
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3031056
Minimum-0.8
Maximum3.2
Zeros0
Zeros (%)0.0%
Negative3
Negative (%)0.1%
Memory size16.5 KiB
2024-04-21T23:00:49.032193image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-0.8
5-th percentile0.3
Q10.7
median1.2
Q31.7
95-th percentile3
Maximum3.2
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.77981135
Coefficient of variation (CV)0.59842529
Kurtosis-0.037228274
Mean1.3031056
Median Absolute Deviation (MAD)0.5
Skewness0.76503449
Sum2736.5218
Variance0.60810575
MonotonicityNot monotonic
2024-04-21T23:00:49.195300image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8 116
 
5.5%
0.4 113
 
5.4%
1.3 113
 
5.4%
0.5 112
 
5.3%
0.7 110
 
5.2%
0.6 108
 
5.1%
0.9 103
 
4.9%
1.2 97
 
4.6%
1.5 94
 
4.5%
1.4 91
 
4.3%
Other values (123) 1043
49.7%
ValueCountFrequency (%)
-0.8 3
 
0.1%
0.2 45
2.1%
0.250516649 1
 
< 0.1%
0.3 81
3.9%
0.305801033 1
 
< 0.1%
0.359472409 1
 
< 0.1%
0.376735672 1
 
< 0.1%
0.393548218 1
 
< 0.1%
0.397852112 1
 
< 0.1%
0.398390113 1
 
< 0.1%
ValueCountFrequency (%)
3.2 88
4.2%
3.1 10
 
0.5%
3 15
 
0.7%
2.994366442 1
 
< 0.1%
2.9 13
 
0.6%
2.812494354 1
 
< 0.1%
2.8 19
 
0.9%
2.798338103 1
 
< 0.1%
2.715928972 1
 
< 0.1%
2.7 24
 
1.1%

ALTV
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct119
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.7037978
Minimum-16.5
Maximum27.5
Zeros1150
Zeros (%)54.8%
Negative37
Negative (%)1.8%
Memory size16.5 KiB
2024-04-21T23:00:49.356736image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-16.5
5-th percentile0
Q10
median0
Q311
95-th percentile27.5
Maximum27.5
Range44
Interquartile range (IQR)11

Descriptive statistics

Standard deviation10.378137
Coefficient of variation (CV)1.5480981
Kurtosis-0.16807268
Mean6.7037978
Median Absolute Deviation (MAD)0
Skewness1.2092184
Sum14077.975
Variance107.70572
MonotonicityNot monotonic
2024-04-21T23:00:49.507922image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1150
54.8%
27.5 311
 
14.8%
1 48
 
2.3%
2 44
 
2.1%
5 38
 
1.8%
4 38
 
1.8%
3 34
 
1.6%
8 33
 
1.6%
6 30
 
1.4%
12 28
 
1.3%
Other values (109) 346
 
16.5%
ValueCountFrequency (%)
-16.5 3
0.1%
-1.043619084 1
 
< 0.1%
-0.899870498 1
 
< 0.1%
-0.899837444 1
 
< 0.1%
-0.809727159 1
 
< 0.1%
-0.702935751 1
 
< 0.1%
-0.70072341 1
 
< 0.1%
-0.690275646 1
 
< 0.1%
-0.679148077 1
 
< 0.1%
-0.580259763 1
 
< 0.1%
ValueCountFrequency (%)
27.5 311
14.8%
27 8
 
0.4%
26.4281791 1
 
< 0.1%
26.29412507 1
 
< 0.1%
26 5
 
0.2%
25.88886743 1
 
< 0.1%
25 11
 
0.5%
24 4
 
0.2%
23 8
 
0.4%
22 13
 
0.6%

MLTV
Real number (ℝ)

ZEROS 

Distinct296
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.0168258
Minimum-4.85
Maximum20.35
Zeros124
Zeros (%)5.9%
Negative11
Negative (%)0.5%
Memory size16.5 KiB
2024-04-21T23:00:49.647420image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-4.85
5-th percentile0
Q14.6
median7.4
Q310.9
95-th percentile18.61775
Maximum20.35
Range25.2
Interquartile range (IQR)6.3

Descriptive statistics

Standard deviation5.0974595
Coefficient of variation (CV)0.63584511
Kurtosis-0.03500204
Mean8.0168258
Median Absolute Deviation (MAD)3.1
Skewness0.5157091
Sum16835.334
Variance25.984094
MonotonicityNot monotonic
2024-04-21T23:00:49.819186image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 124
 
5.9%
20.35 76
 
3.6%
7.1 29
 
1.4%
6.7 26
 
1.2%
5.2 23
 
1.1%
6.5 22
 
1.0%
9.5 22
 
1.0%
6.8 22
 
1.0%
7.2 22
 
1.0%
5.3 21
 
1.0%
Other values (286) 1713
81.6%
ValueCountFrequency (%)
-4.85 5
 
0.2%
-0.200787599 1
 
< 0.1%
-0.191511204 1
 
< 0.1%
-0.172074635 1
 
< 0.1%
-0.148959362 1
 
< 0.1%
-0.136052801 1
 
< 0.1%
-0.024397388 1
 
< 0.1%
0 124
5.9%
0.1 3
 
0.1%
0.128830028 1
 
< 0.1%
ValueCountFrequency (%)
20.35 76
3.6%
20.04035414 1
 
< 0.1%
20 1
 
< 0.1%
19.9 2
 
0.1%
19.8 2
 
0.1%
19.7 4
 
0.2%
19.6 3
 
0.1%
19.4 3
 
0.1%
19.33980408 1
 
< 0.1%
19.3 3
 
0.1%

Width
Real number (ℝ)

HIGH CORRELATION 

Distinct261
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70.354568
Minimum-57.5
Maximum194.5
Zeros0
Zeros (%)0.0%
Negative5
Negative (%)0.2%
Memory size16.5 KiB
2024-04-21T23:00:49.997208image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-57.5
5-th percentile16
Q137
median67.243234
Q3100
95-th percentile138
Maximum194.5
Range252
Interquartile range (IQR)63

Descriptive statistics

Standard deviation39.785428
Coefficient of variation (CV)0.56549886
Kurtosis-0.60474952
Mean70.354568
Median Absolute Deviation (MAD)31.756766
Skewness0.28536631
Sum147744.59
Variance1582.8803
MonotonicityNot monotonic
2024-04-21T23:00:50.192820image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39 41
 
2.0%
102 33
 
1.6%
31 29
 
1.4%
27 29
 
1.4%
90 27
 
1.3%
96 25
 
1.2%
98 25
 
1.2%
42 24
 
1.1%
20 24
 
1.1%
38 23
 
1.1%
Other values (251) 1820
86.7%
ValueCountFrequency (%)
-57.5 5
0.2%
3 2
 
0.1%
5 2
 
0.1%
6 1
 
< 0.1%
6.964561015 1
 
< 0.1%
7 3
 
0.1%
8 9
0.4%
9 6
0.3%
10 9
0.4%
10.23422532 1
 
< 0.1%
ValueCountFrequency (%)
194.5 5
0.2%
180 1
 
< 0.1%
176.310998 1
 
< 0.1%
176.0207478 1
 
< 0.1%
176 4
0.2%
163 2
 
0.1%
162 1
 
< 0.1%
161 5
0.2%
158.5742723 1
 
< 0.1%
158 1
 
< 0.1%

Tendency
Real number (ℝ)

ZEROS 

Distinct110
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.31902768
Minimum-1.5
Maximum2.5
Zeros1035
Zeros (%)49.3%
Negative202
Negative (%)9.6%
Memory size16.5 KiB
2024-04-21T23:00:50.353996image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-1.5
5-th percentile-1
Q10
median0
Q31
95-th percentile1
Maximum2.5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.62483286
Coefficient of variation (CV)1.9585538
Kurtosis-0.3736384
Mean0.31902768
Median Absolute Deviation (MAD)0.003862928
Skewness-0.27629022
Sum669.95812
Variance0.39041611
MonotonicityNot monotonic
2024-04-21T23:00:50.532106image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1035
49.3%
1 801
38.1%
-1 149
 
7.1%
-1.5 6
 
0.3%
2.5 4
 
0.2%
0.028815112 1
 
< 0.1%
1.016358595 1
 
< 0.1%
-0.003225882 1
 
< 0.1%
-0.011379128 1
 
< 0.1%
0.028142591 1
 
< 0.1%
Other values (100) 100
 
4.8%
ValueCountFrequency (%)
-1.5 6
 
0.3%
-1.006614223 1
 
< 0.1%
-1.006588731 1
 
< 0.1%
-1.005940428 1
 
< 0.1%
-1.005385046 1
 
< 0.1%
-1.004148101 1
 
< 0.1%
-1.003861156 1
 
< 0.1%
-1.002239422 1
 
< 0.1%
-1.002108482 1
 
< 0.1%
-1 149
7.1%
ValueCountFrequency (%)
2.5 4
0.2%
1.023634941 1
 
< 0.1%
1.021553856 1
 
< 0.1%
1.016483707 1
 
< 0.1%
1.016358595 1
 
< 0.1%
1.016007896 1
 
< 0.1%
1.007938625 1
 
< 0.1%
1.006071494 1
 
< 0.1%
1.005187563 1
 
< 0.1%
1.004427557 1
 
< 0.1%

Interactions

2024-04-21T23:00:45.595500image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:33.329695image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:34.684162image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:35.894641image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:36.977854image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:38.129386image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:39.998230image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:41.110546image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:42.333657image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:43.396627image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:44.503439image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:45.697936image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-04-21T23:00:34.793980image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:35.992074image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-04-21T23:00:40.104057image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-04-21T23:00:37.176554image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-04-21T23:00:38.497129image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:40.300365image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-04-21T23:00:46.048194image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:33.876784image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:35.140272image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:36.278515image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:37.386088image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:38.617156image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:40.410418image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:41.567568image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-04-21T23:00:35.272780image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-04-21T23:00:40.523233image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-04-21T23:00:46.262256image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:34.125438image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:35.370279image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:36.465875image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:37.593073image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-04-21T23:00:40.613133image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:41.773949image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:42.906226image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:43.990745image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:45.106048image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:46.373944image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:34.243164image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:35.482976image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-04-21T23:00:43.006386image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:44.103271image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:45.217322image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-04-21T23:00:34.339329image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:35.569172image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:36.674519image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:37.802401image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:39.055061image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:40.815864image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:41.978498image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:43.106222image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:44.187171image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:45.298681image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:46.578305image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:34.462828image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:35.670395image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:36.767163image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:37.902957image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:39.185161image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:40.910462image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:42.092289image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:43.197545image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:44.297702image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:45.397265image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:46.682911image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:34.567222image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:35.771013image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:36.857301image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:38.005868image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:39.888866image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:41.004279image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:42.206706image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:43.287677image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:44.387420image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-21T23:00:45.492355image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2024-04-21T23:00:50.665249image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ACALTVASTVDLFMLBMLTVMSTVTendencyUCWidth
AC1.000-0.458-0.334-0.0190.038-0.112-0.1020.308-0.0220.1200.337
ALTV-0.4581.0000.396-0.361-0.0660.330-0.039-0.6520.065-0.270-0.504
ASTV-0.3340.3961.000-0.1500.2610.308-0.334-0.510-0.000-0.209-0.273
DL-0.019-0.361-0.1501.0000.023-0.168-0.2310.5960.0660.2860.566
FM0.038-0.0660.2610.0231.000-0.015-0.1100.047-0.004-0.3080.166
LB-0.1120.3300.308-0.168-0.0151.000-0.053-0.3560.281-0.143-0.151
MLTV-0.102-0.039-0.334-0.231-0.110-0.0531.000-0.0180.121-0.0700.049
MSTV0.308-0.652-0.5100.5960.047-0.356-0.0181.000-0.0400.3200.701
Tendency-0.0220.065-0.0000.066-0.0040.2810.121-0.0401.000-0.0790.146
UC0.120-0.270-0.2090.286-0.308-0.143-0.0700.320-0.0791.0000.132
Width0.337-0.504-0.2730.5660.166-0.1510.0490.7010.1460.1321.000

Missing values

2024-04-21T23:00:46.840432image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T23:00:47.026011image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

LBACFMUCDLASTVMSTVALTVMLTVWidthTendency
0120.0000000.0000000.00.0000000.00000073.00.527.52.4064.0000000.999926
1132.0000000.0063800.00.0063800.00319017.02.10.010.40130.0000000.000000
2133.0000000.0033220.00.0083060.00332216.02.10.013.40130.0000000.000000
3134.0000000.0025610.00.0077420.00256116.02.40.020.35117.0000001.000000
4131.9482320.0065150.00.0081430.00000016.02.40.019.90117.0000001.000000
5134.0000000.0011160.00.0104930.00823726.03.20.00.00150.0000000.000000
6134.0000000.0014030.00.0126230.00823729.03.20.00.00150.0000000.000000
7122.0000000.0000000.00.0000000.00000083.00.56.015.6069.9202611.000000
8122.0000000.0141240.00.0015170.00000084.00.55.013.6068.0000001.000000
9122.0000000.0000000.00.0029670.00000086.00.36.010.6068.0000001.000000
LBACFMUCDLASTVMSTVALTVMLTVWidthTendency
2090140.00.0039680.0000000.0039680.00000080.00.227.5000002.218.00.000000
2091140.00.0000000.0000000.0078120.00000079.00.320.0000008.526.01.002932
2092140.00.0000000.0000000.0064700.00089879.00.526.4281797.021.01.000000
2093140.00.0000000.0000000.0067640.00112779.00.627.0000006.426.01.000000
2094140.00.0000000.0000000.0049750.00124477.00.717.0000006.031.00.000000
2095140.00.0000000.0063980.0074260.00000079.00.225.0000007.240.00.000000
2096140.00.0007750.0000000.0069790.00000078.00.422.0000007.166.01.000000
2097140.00.0009800.0000000.0068630.00000079.00.420.0000006.167.01.000000
2098140.00.0006790.0000000.0061100.00000078.00.427.0000007.066.01.000000
2099142.00.001616-0.0001880.0080780.00000074.00.427.5000005.042.00.000000